app.py

# imports fastbook for Fast.AI, as well as relevant dependencies

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
import os
import fastbook
fastbook.setup_book()

from fastbook import *

learner = load_learner('jianyang.pkl')

categories = ('Not a Hotdog', 'Hotdog')

def is_hotdog(img):

    prediction, prediction_index, probabilities = learner.predict(img)
    dictionary = dict(zip(categories, map(float, probabilities)))

    if dictionary['Hotdog'] < 0.3:
        dictionary['Not a Hotdog'] = 1
        dictionary['Hotdog'] = 0

    return dictionary

import gradio as gr

image = gr.inputs.Image(shape = (192, 192))
label = gr.outputs.Label()
examples = ['pizza.jpg', 'hotdog.jpg']
intf = gr.Interface(fn=is_hotdog, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)